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FtsZ is a promising target for developing new antibacterials. A cell-based screen was developed and used to understand the mechanism of resistance to PC190723. It is reported for the first time that salt bridge interactions within the FtsZ structure prevent PC190723 binding and PC190723 targets FtsZ from a Gram-negative bacterium such as Helictobacter pylori.

Elastic Full wave-field (eFWI) inversion is aimed at inferring physical properties of the subsurface directly from seismic data. Goal is use highest level of physics to produce reliable properties to impact upstream business decisions. We focus on elastic parameters particularly the ratio between pressure (P) and shear (S) wave velocity, Vp/Vs that can be indicative of the type of fluid present in subsurface reservoir and P-wave impedance, Ip to impact porosity estimation.Our eFWI methodology derives the wavelet directly from seismic shots rather than using well information. Using field examples we explain the eFWI workflow, outline key steps and provide analysis of the results. The first field example is from a structurally simple clastic setting. The second field example is from a complex sub-salt environment and is focused on differentiating net versus non-net in pre-salt carbonate reservoirs - a challenging problem when using narrow azimuth streamer data. The third field example is from a clastic setting and uses well information to scale the wavelet and is applicable in development and production settings.Our experiments with the two exploration style field examples show that it is possible to directly invert shot data to obtain geologically meaningful elastic properties useful in exploration and early development phases. However, challenges remain. The inverted Ip has higher fidelity compared to the Vp/Vs ratio. In fact, Ip is sufficiently accurate to be reliably used for porosity prediction. The eFWI Vp/Vs inversion results are only in qualitative agreement with well information (as a blind test) for the clastic example, but sufficient to discriminate the net versus non-net for the pre-salt example. A qualitative match may be insufficient to determine fluid type via rock property inversion without any well control. In an environment without well control, further research is needed to investigate the sensitivity of Vp/Vs and determine if data quality is a key factor, in addition to stabilizing the extraction of elastic parameters in a multi-parameter inverse problem.The novel aspect for our approach is in developing a practical eFWI methodology in 3D and working with raw seismic shots with very minimal processing. Examples from different geological settings and use of well versus no-well provide valuable insights into current application space and potential research direction on improvements to eFWI algorithm.

Bacterial cell division proteins, especially the tubulin homolog FtsZ, have emerged as strong targets for developing new antibiotics. Here, we have utilized the fission yeast heterologous expression system to develop a cell-based assay to screen for small molecules that directly and specifically target the bacterial cell division protein FtsZ. The strategy also allows for simultaneous assessment of the toxicity of the drugs to eukaryotic yeast cells. As a proof-of-concept of the utility of this assay, we demonstrate the effect of the inhibitors sanguinarine, berberine and PC190723 on FtsZ. Though sanguinarine and berberine affect FtsZ polymerization, they exert a toxic effect on the cells. Further, using this assay system, we show that PC190723 affectsHelicobacter pyloriFtsZ function and gain new insights into the molecular determinants of resistance to PC190723. Based on sequence and structural analysis and site-specific mutations, we demonstrate that the presence of salt-bridge interactions between the central H7 helix and beta-strands S9 and S10 mediate resistance to PC190723 in FtsZ. The single-stepin vivocell-based assay using fission yeast enabled us to dissect the contribution of sequence-specific features of FtsZ and cell permeability effects associated with bacterial cell envelopes. Thus, our assay serves as a potent tool to rapidly identify novel compounds targeting polymeric bacterial cytoskeletal proteins like FtsZ to understand how they alter polymerization dynamics and address resistance determinants in targets.

Controlling noise pollution in smart cities is a big challenge nowadays due to rise in urbanization and industrialization. As population mass grows, the celebration of yearly festivals such as Dussehra in Bhubaneswar city is also getting popular. However, since this sound pollution is creating a risk to human health, regular monitoring is strictly needed. In this work, the noise pollution level of Bhubaneswar smart city during Dussehra 2020 is predicted using different supervised machine learning (ML) prediction models. The input parameters considered for this work are area or zones of Bhubaneswar city, time at which sound level recorded, equivalent continuous sound level (Leq in dBA), and noise level (high/low compared to the standard value). The data collected for training phase and testing phase by using different ML models is taken from State Pollution Control Board, Odisha, India, for the years 2015–2020. The supervised ML models taken in this work are Decision Tree (DT), Neural Network (NN), k-Nearest Neighbor (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Random Forest (RF). The predictions of the models are evaluated using Orange 3.26 data analytics tool. From the results, it was found that DT and RF show a higher classification accuracy, 92.5%, than that of other ML models. Moreover, it is observed that the probability of prediction of noise pollution level for the testing dataset for DT is higher for high noise level and for RF is higher for low noise level than other prediction models.

Sequence alignments are models that capture the structural, functional and evolutionary relationships between proteins. Structure-guided sequence alignments are helpful in the case of distantly related proteins with poor sequence identity, thus rendering routine sequence alignment methods ineffective. Protein Alignment organized as Structural Superfamilies or PASS2 database provides such sequence alignments of protein domains within a superfamily as per the Structural Classification of Proteins extended (SCOPe) database. The current update of PASS2 (i.e. PASS2.7) is following the latest release of SCOPe (2.07) and we provide data for 14 323 protein domains that are Database URL The updated version of the PASS2 database is available at http://caps.ncbs.res.in/pass2/.

Background:WFDC1/Prostate stromal 20 (ps20) is a small secreted protein highly expressed within the prostate stroma. WFDC1/ps20 expression is frequently downregulated or lost in prostate cancer (PCa) and ps20 has demonstrated growth-suppressive functions in numerous tumour model systems, although the mechanisms of this phenomenon are not understood.Methods:Ps20 was cloned and overexpressed in DU145, PC3, LNCaP and WPMY-1 cells. Cellular growth, cell cycle and apoptosis were characterised. WPMY-1 stromal cells expressing ps20 were characterised by transcriptome microarray and the function of WPMY-1 conditioned media on growth of PCa cell lines was assessed.Results:Prostrate stromal 20 expression enhanced the proliferation of LNCaP cells, whereas stromal WPMY-1 cells were inhibited and underwent increased apoptosis. Prostrate stromal 20-expressing WPMY-1 cells secrete a potently proapoptotic conditioned media. Prostrate stromal 20 overexpression upregulates expression of cyclooxygenase-2 (COX-2) in LNCaP and WPMY-1 cells, and induces expression of a growth-suppressive phenotype, which inhibits proliferation of PCa cells by ps20-expressing WPMY-1 conditioned media. This growth suppression was subsequently shown to be dependent on COX-2 function.Conclusions:This work posits that expression of ps20 in the prostate stroma can regulate growth of epithelial and other tissues through the prostaglandin synthase pathway, and thereby restricts development and progression of neoplasms. This provides a rational for selective pressure against ps20 expression in tumour- associated stroma.

The functional heterogeneity of T cell responses to diverse antigens expressed at different stages of Mycobacterium tuberculosis (Mtb) infection, in particular early secreted versus dormancy related latency antigens expressed later, that distinguish subjects with latent (LTBI), pulmonary (PTB) or extrapulmonary (EPTB) tuberculosis remains unclear. Here we show blood central memory CD4 T-cell responses specific to Mtb dormancy related (DosR) latency, but not classical immunodominant secretory antigens, to clearly differentiate LTBI from EPTB and PTB. The polyfunctionality score integrating up to 31 DosR-specific CD4 T-cell functional profiles was significantly higher in LTBI than EPTB or PTB subjects. Further analysis of 256 DosR-specific T-cell functional profiles identified regulatory IL10 + Th17 cells (IL10+IL17A+IL17F+IL22+) to be significantly enriched in LTBI; in contrast to pro-inflammatory Th17 cells (IFNγ+IL17A+/IL10−) in the blood and lung of EPTB and PTB subjects respectively. A blood polyfunctional, Mtb DosR latency antigen specific, regulatory, central memory response is therefore a novel functional component of T-cell immunity in latent TB and potential correlate of protection.

The functional heterogeneity of T cell responses to diverse antigens expressed at different stages of Mycobacterium tuberculosis (Mtb) infection, in particular early secreted versus dormancy related latency antigens expressed later, that distinguish subjects with latent (LTBI), pulmonary (PTB) or extrapulmonary (EPTB) tuberculosis remains unclear. Here we show blood central memory CD4 T-cell responses specific to Mtb dormancy related (DosR) latency, but not classical immunodominant secretory antigens, to clearly differentiate LTBI from EPTB and PTB. The polyfunctionality score integrating up to 31 DosR-specific CD4 T-cell functional profiles was significantly higher in LTBI than EPTB or PTB subjects. Further analysis of 256 DosR-specific T-cell functional profiles identified regulatory IL10 + Th17 cells (IL10+IL17A+IL17F+IL22+) to be significantly enriched in LTBI; in contrast to pro-inflammatory Th17 cells (IFNγ+IL17A+/IL10−) in the blood and lung of EPTB and PTB subjects respectively. A blood polyfunctional, Mtb DosR latency antigen specific, regulatory, central memory response is therefore a novel functional component of T-cell immunity in latent TB and potential correlate of protection.